Machine Learning for LIfe Science (MLLS), Department of Biology
Faculty of SCIENCE, University of Copenhagen


The Machine Learning for LIfe Science (MLLS) Center invites applications for a Ph D Fellow position starting in October 2024, or as soon as possible after that. The position is within the scope of MLLS and the CAZAI project, both of which are funded by the Novo Nordisk Foundation Data Science Initiative. The Department of Biology and the Pioneer Centre for AI, Faculty of Science at University of Copenhagen will host the Ph D candidate.

About the MLLS Center
The Machine Learning for Life Science Center is currently funded by the Novo Nordisk Foundation until the end of 2026. The principal investigators are from the Department of Computer Science and Biology, University of Copenhagen and DTU Compute, Technical University of Denmark and all are working on machine learning methodology inspired by applications in life and natural sciences. The Pioneer Centre for Artificial Intelligence at University of Copenhagen serves as host for the Center’s activities.

For more information on the Center's activities and researchers, please see http://mlls.dk .

About the CAZAI project
Cazyme specificity prediction using AI (CAZAI) is a collaborative research project headed by professor Bernard Henrissat, DTU Bioengineering, Technical University of Denmark (DTU) with Co-PIs, professor Ole Winther, Department of Biology, University of Copenhagen (UCPH) and Research engineer Renaud Vincentelli, Aix-Marseille University. CAZAI is funded by the Novo Nordisk Foundation and runs until the end of 2027. The project aims at improving the functional characterization of carbohydrate-active enzymes through predictive machine learning and experimental data collection and validation.

The advertised position will have Ole Winther as main supervisor.

The Ph D project
The Ph D position aims at

Who are we looking for?
The ideal candidate has a background in machine learning, with an MSc preferably in bioinformatics, computational biology, or a related field. The candidate has a strong motivation for doing multidisciplinary research as well as for developing machine learning models to advance the state of the art in biological sequence analysis.

Research projects will involve developing language model-based prediction methods for translation initiation site prediction in a phylogenetically broad spectrum of organisms all across the Tree of Life. The projects will include advancing models for sequence-based predictions in general, and for carbohydrate-active enzymes.

Furthermore, the projects will encompass thorough data curation pipelines based on several biological databases, executing various systematic analyses of biological data, and performing experiments related to finetuning of large language models trained on biological sequences.

To qualify for this position, you should have a number of the following qualifications:

• Curious mindset with a strong interest in the research themes of MLLS and CAZAI.
• Knowledge and experience in working with protein language models.
• Strong programming skills in Python, with a particular focus on experience in Py Torch.
• Experience with carrying out a bioinformatics workflow pipeline, including thorough data curation, analysis and modeling.
• Experience with Linux, including working in high-performance computing environments.
• Strong background in biology, including knowledge of phylogeny and taxonomy.
• Analytical mindset and ability to work systematically.
• Great ability to work both independently as well as in collaborations.
• Excellent English language skills.
• University-level teaching experience is a plus.

The Ph D programme
The Ph D programme offered is three years of full-time study within the framework of the regular Ph D programme (5+3 scheme) .

Qualifications needed: To be eligible for the regular Ph D programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. Computer science, Machine learning, Bioinformatics or other related technical disciplines. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database .

Terms of employment in the regular programme
Employment as Ph D fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a Ph D student at the Ph D School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The terms of employment and salary are in accordance with the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in the Ph D programme

• Carry through an independent research project under supervision

• Complete Ph D courses corresponding to approx. 30 ECTS / ½ FTE

• Participate in active research environments, including a stay at another research institution, preferably abroad

• Teaching and knowledge dissemination activities

• Write scientific papers aimed at high-impact journals

• Write and defend a Ph D thesis on the basis of your project
  

We are looking for the following qualifications:

• Professional qualifications relevant to the Ph D project

• Relevant work experience

• Relevant publications

• Other relevant professional activities

• Curious mind-set with a strong interest in the research themes of MLLS and CAZAI

• Excellent English language skills

Application and Assessment Procedure
Your application, including all attachments, must be in English and submitted electronically by clicking APPLY NOW below.

Please include :

Application deadline:

The deadline for applications is 30 September 2024, 23:59 CEST.

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process
After the deadline, a number of applicants will be selected for academic assessment by an unbiased expert assessor. You are notified whether you will be passed for assessment.

The assessor will assess the qualifications and experience of the shortlisted applicants with respect to the above-mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/ .

Interviews with selected candidates are expected to be held in October 2024.

Questions
For specific information, please contact Ole Winther ( ole.winther@bio.ku.dk ).

General information about Ph D study at the Faculty of SCIENCE is available at the Ph D School’s website: https://www.science.ku.dk/phd/ .

The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.